Data Engineer, Data Platform
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Engineer, Data Platform based in Brazil.
This is an opportunity for a Data Engineer to join a high-impact Data Platform team building the foundation that powers analytics, AI, and machine learning at scale.
You will work on a modern and evolving data ecosystem, contributing to the design and evolution of large-scale data infrastructure.
The role is hands-on and ownership-driven, covering the full lifecycle of data — from ingestion and processing to storage and consumption.
You will help shape a next-generation data platform transitioning toward a modern lakehouse architecture.
The environment is highly technical, fast-evolving, and strongly focused on impact, quality, and scalability.
You will collaborate with experienced engineers while having autonomy to own meaningful initiatives end-to-end.
This is a role for someone who enjoys solving complex data problems and building systems that others rely on.
Accountabilities:
- Design, build, and evolve scalable data pipelines supporting ingestion, transformation, and consumption across the platform.
- Own end-to-end data engineering initiatives, from architecture design to production deployment and monitoring.
- Support the migration and evolution toward a modern data lakehouse architecture using open table formats.
- Develop and optimize batch and streaming data processing systems for large-scale event ingestion.
- Contribute to the design and improvement of data modeling, storage strategies, and consumption layers.
- Work with cloud-based infrastructure to ensure performance, reliability, and scalability of data systems.
- Collaborate with cross-functional teams to define data needs, standards, and best practices.
- Participate in on-call rotation and support operational stability of critical data platform components.
- Strong experience as a Data Engineer, Analytics Engineer, Data Platform Engineer, or similar role.
- Proficiency in Python and SQL, with experience in building production-grade data pipelines.
- Experience working with modern cloud data platforms (AWS preferred; GCP or Azure also valued).
- Solid understanding of data architectures such as data warehouses, data lakes, and lakehouse models.
- Experience with distributed data processing and large-scale data systems.
- Ability to design and build reliable, idempotent, and well-documented data workflows.
- Strong problem-solving skills with the ability to handle ambiguous technical challenges independently.
- Experience working in cross-functional engineering environments with strong communication skills.
- Nice to have: experience with Kafka, Kinesis, Flink, Spark, Kubernetes/EKS, Terraform, and open table formats like Apache Iceberg, Delta Lake, or Hudi.
- Familiarity with data governance, observability, and building data APIs is a plus.
- Strong written communication skills for technical documentation, specifications, and design notes.
- Competitive compensation with potential equity participation
- Health, dental, and life insurance coverage
- Annual budget for professional development in technology
- Language learning support (English, Spanish, Portuguese)
- Flexible meal allowance
- Extended parental leave and childcare assistance
- Remote-first culture with flexible work schedule
- Home office financial support and setup assistance
- Wellness and employee support programs
- Annual profit-sharing program.
Requirements:
Benefits:
Data & ML pay context
Based on 1,554 disclosed Data & ML salaries on RoleSuite, the role pays a median of $162K/year, with most offers between $127K and $201K (10th–90th percentile: $106K–$244K).
See the full Data & ML salary breakdown →